We consider the problem of identifying automatic translations from manual translations of the same sentence. Using two different similarity metrics (BLEU and Levenshtein edit distance), we found out that automatic translations are closer to each other than they are to manual translations. We also use phylogenetic trees to provide a visual representation of the distances between pairs of individual sentences in a set of translations. The differences in lexical distance are statistically significant, both for Chinese to English and for Arabic to English translations.